The basics of graph technology are that each entity (e.g. person, place, object) is characterised by a node, which is connected by an edge to another entity. The edge represents the relationship between them. Each node can be linked to many others and always at least one because there are no broken links. Therein lies the beauty of graph. The acknowledgement that data does not exist in isolation but requires a framework of reference to be of value. The infinite power of relationships maximises the intelligence of a single data point by providing the context to understand its significance within your digital environment.
Consider a name on a mailing list. It could be anyone and has absolutely no value to you until it is linked to something else, e.g. a request, purchase, complaint or website browse. This association immediately provides you with more insight than you had before. Obviously, the more information connected to that identity the clearer the picture of that person’s potential value to your company – and how to optimise it.
The value of connected data
The deluge of data flooding companies daily is relatively simple to collect and even store. The real issue is how to synthesise it into business value, which is where connected data comes in. When analysed effectively it can reveal a myriad of insights into product development, customer experience, operational efficiency, vulnerabilities and much, much more. Its potential is immense, from providing a bespoke customer experience to dynamic control of your supply chain to bringing down fraud syndicates.
There are two distinct aspects to connecting your data:
1. Breaking down technological and departmental siloes.
2. Joining up data points and data sets to create a pattern of interactions for in-depth analysis.
The first requires a suitable data source agnostic platform to ingest all of your data, structured and unstructured, from point solutions and third party applications into a central repository. Ideally it will cater for streaming and batched data, in high volumes, which requires a Lambda architecture. This end-to-end visibility allows each department access to relevant information to assist customers, develop new products and services, improve operations, pre-empt potential issues, etc.
The second needs a lot more expertise to optimise your data intel because the true value in connected data is its relationship to everything else. This is what provides the context required for effective decision-making. That complaining customer has had a really bad run with us, we need to do better. Or, that customer complains about everything in order to get discounts and freebies. Knowing the difference affects your decision.
Top analysts have been singing the praises of graph database technology for the last few years as it is the ideal solution for storing and analysing highly-connected data points in complex environments. It’s capacity to rapidly discover hidden patterns and trends means that its applications are practically limitless!
The benefits of graph
The most effective way to connect data points and data sets is by using graph technology and there are a multitude of reasons why. Graph:
• Prioritises relationships: these are stored with the individual object / node providing an immediate interrelated accessibility that surpasses traditional databases.
• Is flexible: Relationships are not pre-defined and the structure can be built as data is ingested. This provides an agile database with a schema that can evolve with your company without compromising your existing network.
• Can handle an extensive amount of complexity and variation in these relationships, making it ideal for machine learning (ML) and AI related operations.
• Reveals the hidden patterns and provides context, including examining the dynamic, complex or unusual relationships between data, e.g. fraud detection, supply chain visibility.
• Takes advantage of the fetch-execute cycle to perform queries quicker, including reciprocal ones. E.g. What items did a customer buy? Then, which other customers bought this product(s)?
• Is an adaptable and extremely flaw-tolerant system.
• Has wide-ranging capabilities and applications.
intelligence . illuminated ®
So, the point of connecting your data is to obtain intelligence, i.e. value-added information, to assist with decision-making, product and service development, operational efficiency, risk mitigation, etc. Graph technology will take you most of the way there but it excels in accuracy and insight generation when it collaborates with its friends.
Locstat LightWeaver® unites graph with a range of other capabilities to provide next-generation solutions. These include complex event processing and a client facing rules engine, computation, recommendation and segmentation engines; AI and ML operations, to perform graphAI and graphML with ease; natural language processing (NLP) and geospatial processing engines. Our unique and powerful graph analytics platform transforms your data into business value, ensuring you retain the competitive advantage and providing a springboard to fulfil your organisation’s incredible potential.